Compare multiple metrics on one Shopify chart

And that’s usually where the real decisions live. In the relationship between numbers, not the numbers in isolation.

Shopify finally made this much easier. You can now plot multiple metrics on the same chart in Analytics. Up to 4 metrics on a single line chart, or use the newer Bar and line visualization to compare a “volume” metric and a “rate” metric side by side. No more constant toggling.

This post walks through what it is, where to find it, how to set it up, and the one thing that trips almost everyone up at first. Y axis scaling, especially when you mix dollars and percentages.

Why comparing multiple metrics on one Shopify chart is worth doing

Most Shopify dashboards still kind of nudge you toward one metric at a time. One card for sales. One for sessions. One for conversion rate. That’s fine for monitoring. But decisions are rarely that clean.

Because when sales jump, you immediately want to know :

Was it more traffic, or better conversion ?

Was AOV up, or did we simply sell more units ?

Was it a real improvement, or just a promo spike that will turn into refunds later ?

That’s the core idea behind multi metric charts.

You can :

• Add up to 4 metrics to a line chart so you can see how they trend together.
• Use a Bar and line chart to show one metric as bars and another as a line, which is perfect when you want to compare volume vs efficiency in one view.

And by the end of this post you’ll know :

• Where to find these multi metric options inside Shopify Analytics
• How to add and compare metrics quickly
• How to interpret Y axis behavior when you mix $ totals, counts, and percentages

Quick examples that come up constantly :

• Total sales + Conversion rate
• Sessions + Orders
• AOV + Total sales

Know the building blocks : Shopify Analytics charts, visualization types, and metric “value types”

Before you start stacking metrics on one chart, it helps to know what Shopify is actually showing you, and where.

A quick map of Shopify Analytics areas, just enough to keep the rest of this simple :

• Dashboards : Your top level view, usually a collection of cards.
• Dashboard cards : Individual tiles that show a metric, trend, or small chart.
• Reports : Standard Shopify reports (Sales, Acquisition, Behavior, etc) that can sometimes be customized.
• Explorations : The flexible area where you can build charts more freely, choose dimensions, add metrics, switch visualizations.
• Saved reports : A customized report or exploration you saved so you can come back to it without rebuilding.

Now the visualization types you’ll see mentioned in this post :

• Line chart : Best for trend over time. Now supports up to 4 metrics on one chart.
• Bar chart : Good for comparing totals across categories or time buckets.
• Bar and line (combo) : One metric displayed as bars, the other as a line. Great for “volume + rate” pairings.

And here’s the part people skip, then get confused.

Metric “value types” (why they matter)

Shopify metrics come in different value types :

• Dollars : Total sales, gross sales, net sales, etc
• Counts : Orders, sessions, add to carts, returning customers
• Rates / percentages : Conversion rate, repeat customer rate, etc

Why it matters : the scales are totally different. A chart that mixes $50,000 and 2.3% can easily mislead you if you don’t understand what the Y axis is doing.

Good news though. Shopify’s updated multi metric line charts handle this better now. Metrics with different value types (like dollar totals and percentages) automatically get their own Y axis scale. Still, you need to read labels carefully. Do not just eyeball the lines.

Also, depending on chart type and which metrics you pick, Shopify may handle axes a bit differently. So treat the chart like an instrument panel. Look at the units.

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Where to find multi metric charts in Shopify Analytics (the “paths” that usually work)

Shopify has made multi metric charting available in :

• Explorations
• Saved reports
• Dashboard cards

But how you get there depends on where you start.

Option A : Start from a Dashboard card

This is the easiest path when you already have a card close to what you want.

1. Open Analytics and go to your Dashboard
2. Click the relevant card
3. Open View details or the underlying report
4. If the report supports it, switch the visualization to Line or Bar and line
5. Add or compare metrics from the configuration panel (usually checkboxes)

If you hit a wall and the report feels “locked”, jump to Explorations. That’s usually the escape hatch.

Option B : Use Explorations (most flexible)

Explorations is where you go when you want to actually build something.

• Create or open an exploration
• Choose a date range and the main dimension (often time)
• Add multiple metrics
• Pick a visualization : line or bar and line

This is also where Shopify’s new setup feels the most natural.

Option C : Open a report, customize, then save

Sometimes a standard report already has the right filters and structure, you just need to add the comparison.

• Open a relevant report (Sales, Acquisition, Conversion)
• Customize it (add a secondary metric if supported)
• Save it as a saved report so you can reuse it every week

Small heads up : availability can vary by Shopify plan and by report type. If you can’t add the metric you want in a standard report, don’t fight it for 20 minutes. Try Explorations.

How to plot multiple metrics on one Shopify chart (step by step workflow)

This is the workflow that stays sane. It keeps you from building charts that look fancy but tell you nothing.

Step 1 : Pick the right primary metric

Start with the metric that matches the question.

• Revenue growth question : Total sales (or Net sales, depending on your preference)
• Efficiency question : Conversion rate, AOV, ROAS (if available via integrations)
• Traffic quality question : Sessions, Conversion rate, Orders
• Funnel performance question : Add to cart, Reached checkout, Conversion rate (depends what Shopify exposes for your setup)

Step 2 : Add a second (and maybe third) metric that explains “why”

This is the heart of it.

Examples that work almost every time :

• Total sales + Conversion rate
• Sessions + Conversion rate
• Orders + AOV
• Total sales + Orders (then you infer AOV movement)

In Shopify’s new multi metric line charts, you can add up to 4 metrics using the checkboxes in the config panel. My advice though. Start with 2. Add a third only if it answers a specific follow up question.

Step 3 : Choose the best visualization

• Use a multi metric line chart when you want to see two or more metrics trend together over time.
• Use Bar and line when you specifically want one metric to feel “bigger” and more volumetric (bars), and the other to sit on top as an efficiency signal (line).

Classic example : Total sales (bars) + Conversion rate (line). It just reads well.

Step 4 : Set the same time granularity

Daily vs weekly vs monthly changes the story.

If you plot sales daily and conversion rate daily, you’ll see noise. Especially if you have lower volume days or spiky campaigns. Sometimes weekly is the honest view.

Pick one granularity and stick to it while comparing. If you change it, you can totally change what looks like a “trend”.

Step 5 : Validate what you’re seeing

Before you interpret anything :

• Hover tooltips and check values on specific dates
• Use the legend to toggle metrics on and off
• Confirm your date range is what you think it is
• Watch out for whether Shopify is summing vs averaging, especially for rate metrics

Rates are the big one. A conversion rate over a period is not something you “sum”. It’s usually calculated as a rate based on totals in that window, or an average of smaller buckets. Shopify will generally do the right thing, but you should still confirm by checking definitions and tooltips.

Step 6 : Save it for reuse

Once the chart is actually useful :

• Save as a saved report (good for weekly review)
• Optionally pin/add it to your dashboard as a card

If it’s a KPI you care about every week, get it out of your head and into a reusable saved view. Future you will be grateful.

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Understanding Y axis scaling (especially when mixing dollars, counts, and percentages)

This is the part that causes the most bad reads.

You add Total sales and Conversion rate to the same chart and the conversion line looks dead flat. Like nothing is happening.

But conversion might be moving from 1.8% to 2.4% which is huge. It just looks small next to thousands of dollars.

So what do you do ?

What to look for on the chart

• Check axis labels and units
• Look for whether Shopify is using separate scales for different value types

With Shopify’s updated multi metric line charts, metrics with different value types (like $ and %) automatically get their own Y axis scale. That helps a lot. But you still need to notice it. The chart will not yell at you.

Temporarily hide one metric

Use the legend toggle to hide sales and inspect conversion alone, then bring sales back. This sounds basic, but it stops a lot of misinterpretation.

Be extra careful with rate metrics

Conversion rate is usually calculated as a rate over the period, not a sum of daily rates. If your chart is grouped weekly, the weekly conversion rate is typically based on that week’s totals.

So when something looks “off”, don’t argue with the line. Hover and read the tooltip. Check the metric definition in Shopify.

The goal is clarity, not cramming

Two metrics is often enough for one chart.

When you go beyond that, you’re usually mixing “why” signals together and your brain starts seeing patterns that are not real. If you truly need four metrics, it can work, just slow down and toggle lines on and off while reading.

High signal metric pairings to compare (with what each pairing tells you)

These are pairings I’d actually put on a dashboard, because they tend to lead to action.

Total sales + Conversion rate

What it tells you : whether revenue changes are driven by efficiency or just volume.

• Sales up, conversion flat : likely more traffic, higher AOV, or promos.
• Conversion up, sales flat : maybe traffic dropped while efficiency improved. Or inventory constraints.
• Both up : that’s usually a clean win.

What you might do next : look at PDP changes, checkout friction, offer tests, or traffic mix by channel.

Total sales + Orders

What it tells you : helps you infer AOV shifts without even plotting AOV.

• Sales up, orders flat : AOV likely increased (pricing, bundles, upsells, shipping threshold changes).
• Orders up, sales flat : AOV likely dropped (discounting, lower priced items selling more).

What you might do next : check discount usage, product mix, bundling performance.

AOV + Conversion rate

What it tells you : the classic trade off chart.

• AOV up, conversion down : maybe your offer got more expensive, or you pushed bundles too hard.
• AOV down, conversion up : discounting might be working, but you might be buying revenue.

What you might do next : adjust free shipping thresholds, test bundle presentation, refine pricing and discount strategy.

Refunds/returns (if available) + Total sales

What it tells you : whether growth is being clawed back later.

If sales are up but refunds are also climbing, you may have a product expectation issue, shipping damage, sizing problems, or support bottlenecks.

What you might do next : tighten product pages, improve sizing guides, review shipping packaging, audit post purchase emails and support.

Using Explorations vs saved reports vs dashboard cards : what to use when

They all matter. They just have different jobs.

Explorations

Best for : ad hoc analysis, experimenting, asking “why did this happen ?”

If a standard report won’t let you add the metrics you need, Explorations is usually where you can build the view you want. It’s also the best place to try the new Bar and line visualization.

Saved reports

Best for : repeatable analysis, weekly reviews, campaign post mortems.

A small tip that saves time : use naming conventions like :

• “Weekly Sales vs CVR”
• “Sessions vs Orders (Daily)”
• “AOV vs CVR (Last 90 days)”

And keep date presets consistent when you can, so you are not reinterpreting a new window every time.

Dashboard cards

Best for : quick monitoring.

Keep cards focused. One to two comparisons per card, max. Otherwise dashboards become noisy, and people stop trusting them.

A solid workflow is :

Explore → refine metric pairings + visualization → save report → pin as dashboard card

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Common mistakes that make multi metric charts misleading (and how to avoid them)

This is where most teams get tripped up, even smart ones.

Comparing metrics with incompatible meanings

Not every metric is meant to be read alongside another. If you don’t understand how it’s calculated, you can end up drawing the wrong conclusion.

Fix : check the metric definition in Shopify, especially for rates.

Changing date ranges and forgetting

A “drop” might just be partial period data. Like comparing a full month to the current month on day 6.

Fix : make sure you’re comparing comparable windows. Or use “previous period” comparisons carefully.

Reading percentage metrics as additive

Conversion rate is not additive across time the way sales is. It’s a ratio. Treat it that way.

Fix : confirm in tooltips and definitions whether Shopify is showing an average, a period rate, or something else.

Overloading the chart with too many lines

Four metrics is possible. It’s also how you create a spaghetti chart that convinces you of something that isn’t real.

Fix : start with two. Add a third only if it answers a specific question.

Not checking filters before making a call

If your chart is filtered to one channel, one region, or one device type, the trend might not generalize.

Fix : verify filters. Add segmentation only when you need it, not by default.

Wrap up : a simple checklist for clean multi metric Shopify charts

Use this every time you build one :

1. Pick one question
2. Choose 2 related metrics (maybe 3, rarely 4)
3. Select line chart or Bar and line
4. Confirm Y axis units and scale
5. Align time granularity (daily, weekly, monthly)
6. Sanity check tooltips and metric definitions (especially rates)
7. Save as a saved report
8. Add to dashboard cards if it’s a KPI

The outcome is pretty simple. You see relationships faster, diagnose spikes and dips with less guessing, and you make better decisions inside Shopify Analytics without bouncing between charts all day.

Conclusion

Comparing multiple metrics on one Shopify chart is one of those changes that feels small, but it honestly changes how you work. You stop asking “what happened ?” and you start getting to “why did it happen ?” way quicker.

Use the multi metric line charts when you want trend context, use the Bar and line view when you want volume and efficiency in one glance, and keep an eye on axis labels so you do not get fooled by scale.

Cleaner trend relationships. Faster diagnosis. Better decisions. That’s the whole point.

FAQs (Frequently Asked Questions)